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ICC 2009, Santiago de Chile
Visualization of Glacier Surface MovementSamuel WiesmannInstitute of Cartography, ETH Zurich
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Outline
Introduction Existing visualizations Describing the data in geographic data cube Shortcomings and problems Approach Outlook Conclusions
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Introduction
Visualization of glacier surface movement:
Ice flow: velocities
Changes in ice thickness
Changes in glacier length andice covered area
Mass displacement
(change in shape of crevasses, movement of crevasses, …)
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Existing Visualizations
Velocities: classified and stretched color ramp
[Quincey et al. 2009]
[Giles et al. 2009]
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Geographic Data Cube
The principle I
Time
Variable
Space
point in time (t1)
specific area, e.g. glacier surface
variables from glacier surface (velocity, height, temperature, …)
adopted from [Bahrenberg et al. 1990], [Maidment et al. 2002]
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Situation in a glacier map
Geographic Data Cube
Time
Variable
Space
velocity
heights a.s.l.
direction
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Geographic Data Cube
Type 1: ca. 50% of analyzed visualizations (N=80) fixed space, 1 point in time, 1 to 4 variables
Time
Variable
Space
[Kääb 2005]
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The second type I
Geographic Data Cube
Time
Variable
Space
velocity
heights a.s.l.
direction
point in time (t1)
point in time (t2)
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The second type II
Geographic Data Cube
Time
Variable
Space
velocity
heights a.s.l.
direction
point in time (t1)
point in time (t2)
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Geographic Data Cube
Type 2: ca. 40% of analyzed visualizations (N=80) fixed space, 2 (or more) points in time,
1 to 3 variables (whereof 1 at different times)
[NASA SVS 2006/2009]
Time
Variable
Space
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Geographic Data Cube
Type 1: ca. 50% (N=80)
Type 2: ca. 40%
Type 3: ca. 10%fixed space, time animated, usually 1 variable
Time
Variable
Space
Time
Variable
Space
Time
Variable
Space
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Situation summarized
0% allowing for spatial navigation
0% allowing for thematic navigation
10% allowing for temporal navigation (usually start/stop)
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Problems which arise
Overlaying symbols when comparing: e.g. feature tracking: 4 positions (X/Y), 4 values
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Approach
Intended system architecture
DBMS
PostgreSQLand PostGIS
Preprocessing
Userweb-browser
GIS-Server
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Outlook II
A lot of data from many projects Usually processed for only one publication
Bundle the data and re-use it!
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Outlook III
Compare two glaciers at a certain date Monitor a glacier over a specific time period Compare two glaciers over this period of time
Calculate differences Interpolation
Profiles on-the-fly
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Outlook IV
Integration of glacier simulation models
Extract potentially dangerous areas
Resource when estimating potential natural hazards
… and many more …
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Conclusions
Glaciology mostly uses “classic” cartography Bundle the data! GIS and cartography may provide the platform Underlying technique exists and is ready to adapt Improving the visualization and combining tools More efficient gain of knowledge in glaciology
ICC 2009, Santiago de Chile
Visualization of Glacier Surface MovementSamuel [email protected]
Thank you for your attention